For a Successful Data-driven Transformation, Follow These Three Steps

In this special guest feature, Lars Fæste and Antoine Gourévitch of The Boston Consulting Group, discuss how data is becoming an increasingly powerful tool for business leaders in many industries who want a competitive edge, and how many companies struggle to collect and profit from data in new ways. He then outlines a three-step approach to data transformation that is easier, cheaper and more successful than attempts at sweeping, large-scale change. Lars Fæste is a senior partner and managing director at The Boston Consulting Group, based in Copenhagen, Denmark and the global leader of the firm´s Transformation practice. Antoine Gourévitch is a senior partner and managing director at The Boston Consulting Group, based in Paris, France. He leads the firm´s global work in digital transformation and big data in the Technology Advantage practice.

Companies in a wide range of industries are pursuing data-driven transformation – embedding data collection and analytics throughout their organizations, from sales to marketing, manufacturing, supply chain management and R&D. The business impact can be significant. Business that use data and analytics to reduce waste, to drive performance improvements, and to offer new analytic services to customers, can grow their earnings dramatically – in some cases by 20 to 30 percent a year.

Antoine Gourévitch

But business leaders and IT professionals know that data-driven transformation, like any major IT initiative, can easily go astray. Companies have been known to start their transformation projects by trying to reinvent their core IT systems – usually a multi-year effort that can cost hundreds of millions of dollars. But these centralized efforts take too long and are far too costly; data-driven transformation projects will succeed only if they are cost-effective, incremental, and sustainable.

IT leaders can play a critical role by guiding executive management toward a practical path to data-driven transformation – a path that starts with pilot projects that pay off in weeks or months, then, step two, draws a roadmap for companywide transformation. Finally, in step three, the company spreads digital and data-driven processes and work methods to every corner of the company.

For example, a large industrial company built momentum for transformation through a series of pilots. The first initiatives were in inventory management and capacity optimization. The projects led to significant savings and more sales of high-profit items. In nine months, these quick wins generated $20 million in value.

2. Design the companywide transformation. Lessons from these pilot projects can help inform a roadmap for the companywide transformation. Management must contribute a high-level vision for a portfolio of initiatives to be rolled out in a logical order on the basis of factors such as potential payoff, urgency, and competitive pressure. IT leaders should work to generate consensus on some underpinnings of digital operations – analytics, data governance and data infrastructure. The company also needs to work on industrializing data and analytics – making the capabilities as consistent and reliable as any industrial machinery.

A major logistics company shows how to get it wrong – and how to set it right. Its first attempt to become data-driven involved a top-down IT systems overhaul – one that cost time and resources, and that failed to deliver any operating improvements. The second time around, the company created a detailed roadmap for transformation based on just two considerations: the data needed monthly, weekly and in real time to optimize functions and operations, and the systems and data already available. This led to a series of pilot projects that used existing systems to optimize cost drivers, such as fuel consumption, maintenance, labor, and pricing performance. After dozens of such lean, focused, projects, the company can now call itself data driven – and it leads its industry in earnings.

3. Organize for sustained performance. The success of a data transformation is measured by sustained results. To prepare their organization for a digitized future, companies need to move on four fronts: creating new roles and governance processes, instilling a data-centric culture, adopting new ways of working and cultivating the necessary talent and skills. IT leadership has a part to play on all those fronts – by helping management define the needed roles, working to integrate IT and business teams, and taking the lead on work processes and talent.

Many executives wonder how their organizations can pull off a data-driven transformation, especially when they already complain about a lack of data skills and overburdened IT systems. Using this three-step model can help IT leaders create a roadmap that will help make the gains from digitization stick.

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